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Created page with "== Citation == Mullick, B.; Wang, Y.; Yadav, P. & Farimani, A. B. Learning Super-Resolution Electron Density Map of Proteins using 3D U-Net. Proc. Machine Learning for St..."

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== Citation ==

Mullick, B.; Wang, Y.; Yadav, P. & Farimani, A. B. Learning Super-Resolution Electron Density Map of Proteins using 3D U-Net. Proc. Machine Learning for Structural Biology Workshop, 2020

== Abstract ==

A well-established protein structure is essential for understanding protein molecular
mechanism, phenotypic implication and drug discovery. Recent development of
cryo-Electron Microscopy (cryo-EM) offers the advantage of easy sample preparation and not requiring crystallized protein for structural biology. However, the
resolution of cryo-EM electron density maps used to determine protein structure,
is not at par with X-ray diffraction (XRD) or NMR. In this work, we propose to
leverage a deep learning-based model to increase the resolution of low-quality
electron density maps. The model is built upon U-Net with 3D convolutional
layers, which contains three components: encoder, bottleneck, and decoder. To
get paired maps of different resolutions, we collect high-resolution maps from
XRD as ground truth labels. While the low-resolution maps are obtained through
a noise model which combines dilation operations, Gaussian filters and Gaussian
noise. We also introduce data augmentation techniques during model training, like
random cropping, rotation, and flipping. Experiments show that when applied to
low-resolution electron maps, the U-Net model can improve the resolution in the
metric of EMRinger score, which redesigns the map so that it resolves the regions
of ambiguity to offer greater certainty in the position of amino acids.

== Keywords ==

== Links ==

https://www.mlsb.io/papers/MLSB2020_Learning_Super-Resolution_Electron_Density.pdf

== Related software ==

== Related methods ==

== Comments ==

2020Mullick SuperResolution - Revision history

WikiSysop: Created page with "== Citation == Mullick, B.; Wang, Y.; Yadav, P. & Farimani, A. B. Learning Super-Resolution Electron Density Map of Proteins using 3D U-Net. Proc. Machine Learning for St..."